Head and neck squamous cell carcinoma carries a high mortality rate despite advances in chemotherapy and radiation therapies. This is due mainly to the highly heterogeneous nature of the disease, both morphologically and genetically. A current shortcoming in the diagnosis, prognosis, and treatment of HNSCC is a lack of methods that adequately address the complexity and diversity of the disease. A major objective of the proposed research is to develop a detailed molecular fingerprint of HNSCC tumor tissues that is linked to clinical information. Diagnostic and prognostic marker systems based on single parameters have generally proven inadequate. Thus, multiparametric methods, which rely on many pieces of information, are ideally suited to the grouping of tumor subtypes and the identification of specific patterns of disease progression and clinical outcomes. Our goal is to accomplish a multivariable comprehensive genome-wide molecular blueprint of HNSCC integrated with clinical risk factors in order to refine patient diagnosis and prognosis to aid in the clinical management of patients at the earliest disease stages. We will interrogate an evidence-based panel of gene loci implicated in head and neck cancer, many of which are distributed along critical pathways utilized by HNSCC cells. The molecular targets to be investigated using a novel assay will be done in an epidemiologically well-characterized cohort of 1000 primary HNSCC derived from a large, multi-ethnic, primary care patient population diagnosed by surgical biopsies in the Henry Ford Health System from 1986-2003, and followed from 5-23 years. This approach should yield a validated multivariable genetic blueprint for diagnosis and prognosis analogous to or even more powerful than TNM-staging, permitting more accurate grouping of tumor subtypes, more accurate distinction of prognostic groups, and better prediction of effective treatment strategies.